Abstract
This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.
Highlights
Rising global energy demands and environmental concerns have led to the fast development of renewable energy technologies
Numerous maximum power point tracking (MPPT) techniques have been developed to maximize the PV output power, such as perturb-and-observe (P&O) and incremental conductance (INC) [6,7]. These conventional MPPT methods are appropriate under uniform irradiation conditions [8,9]
This paper presents an accelerated particle-swarm-optimization-based MPPT technique to track
Summary
Rising global energy demands and environmental concerns have led to the fast development of renewable energy technologies. The latter effect makes the conventional MPPT algorithms (such as P&O or INC) difficult to track the global MPP [11,12,13]. Enhancement the INC algorithm that may voltage to find mismatch This strategy is simple and can be applied, but it requires a voltagein find the global MPP by determining all local MPPs. A Fibonacci-based MPPT method is proposed sensor forwhich everyuses. In the abovementioned for MPPT because of its simplicity of simplify the mathematical implementation algorithms, global MPP searching restarting issuefor isPV notsystems discussed, which the is MPPTthe algorithms have been developed to resolve required shading patterns change.as claimed in [34], one particular issue of the PSO based multiplewhen local the problems. PSO strategy is briefly introduced so that particle moves faster toas the global MPP, and at the same time attracts the remaining inparticles
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